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t-Closeness: Privacy Beyond k-Anonymity and l-Diversity
The k-anonymity privacy requirement for publishing microdata requires that each equivalence class (i.e., a set of records that are indistinguishable from each other with respect to certainExpand
Locally Differentially Private Protocols for Frequency Estimation
TLDR
This paper introduces a framework that generalizes several LDP protocols proposed in the literature and yields a simple and fast aggregation algorithm, whose accuracy can be precisely analyzed, resulting in two new protocols that provide better utility than protocols previously proposed. Expand
Design of a role-based trust-management framework
TLDR
The RT framework, a family of role-based trust management languages for representing policies and credentials in distributed authorization, is introduced, and the semantics of credentials are defined by presenting a translation from credentials to Datalog rules. Expand
Distributed Credential Chain Discovery in Trust Management
TLDR
A storage type system for RT0, which guarantees traversability of chains when credentials are well typed, can also help improve search efficiency by guiding search in the right direction, making distributed chain discovery with large number of credentials feasible. Expand
A Study of Probabilistic Password Models
TLDR
This paper finds that Markov models, when done correctly, perform significantly better than the Probabilistic Context-Free Grammar model proposed in Weir et al., which has been used as the state-of-the-art password model in recent research. Expand
Satisfiability and Resiliency in Workflow Authorization Systems
TLDR
This work proposes the role-and-relation-based access control (R2BAC) model for workflow authorization systems, and formally defines three levels of resiliency in workflow systems and study computational problems related to these notions of Resiliency. Expand
Slicing: A New Approach for Privacy Preserving Data Publishing
TLDR
A novel technique called slicing is presented, which partitions the data both horizontally and vertically and can be used for attribute disclosure protection and develops an efficient algorithm for computing the sliced data that obey the ℓ-diversity requirement. Expand
Efficient k -Anonymization Using Clustering Techniques
TLDR
An approach that uses the idea of clustering to minimize information loss and thus ensure good data quality is proposed, and a suitable metric to estimate the information loss introduced by generalizations is developed, which works for both numeric and categorical data. Expand
Differentially private grids for geospatial data
TLDR
This paper proposes a method for choosing a grid size for two-dimensional datasets such as geospatial datasets, and introduces a novel adaptive-grid method, which exploits the need to have finer granularity partitioning over dense regions and, at the same time, coarse partitions over sparse regions. Expand
DATALOG with Constraints: A Foundation for Trust Management Languages
TLDR
The class of linearly decomposable unary constraint domains are defined, it is proved that DATALOG extended with constraints in any combination of such constraint domains is tractable, and it is shown that permissions associated with structured resources fall into this class. Expand
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